df=read_xlsx("Data/sgRNA/Figure5/N100M_sequence_result/N100M_plot.xlsx") %>%
janitor::clean_names()
df <- df %>%
mutate(point_size = ifelse(ladder_type == "Intact", 3.5, 2.5))
ggplot(df, aes(x = monoisotopic_mass/1000, y = apex_rt,
color = log10(sum_intensity),
shape = ladder_type,
group = ladder_type)) +
geom_point(aes(size = point_size)) + # Map size to point_size inside aes()
geom_line(color = "gray34", alpha = 0.5) + # Add lines connecting points within the same ladder_type
scale_x_continuous(name = "Monoisotopic Mass (kDa)", breaks = seq(0, max(df$monoisotopic_mass, na.rm = TRUE), by = 2)) +
scale_y_continuous(name = "Retention Time (min)", limits = c(0,19), breaks = seq(0, 19, by = 2)) +
labs(color = "Log10(Intensity)", shape = "Ladder Type", size = "Ladder Type") + # Add size to legend
theme_classic() +
theme(
axis.title.x = element_text(size = 12),
axis.title.y = element_text(size = 12),
axis.text.x = element_text(size = 10),
axis.text.y = element_text(size = 10),
legend.title = element_text(size = 10),
legend.text = element_text(size = 10)
) +
scale_color_gradientn(colors = turbo(256)) + # Use turbo color scale for the color aesthetic
scale_size_identity() # Use the actual values in point_size for sizing
## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_line()`).

df=read_xlsx("Data/sgRNA/Figure5/N100N_sequence_result/N100N_plot.xlsx") %>%
janitor::clean_names()
df <- df %>%
mutate(point_size = ifelse(ladder_type == "Intact", 3.5, 2.5))
ggplot(df, aes(x = monoisotopic_mass/1000, y = apex_rt,
color = log10(sum_intensity),
shape = ladder_type,
group = ladder_type)) +
geom_point(aes(size = point_size)) + # Map size to point_size inside aes()
geom_line(color = "gray34", alpha = 0.5) + # Add lines connecting points within the same ladder_type
scale_x_continuous(name = "Monoisotopic Mass (kDa)", breaks = seq(0, max(df$monoisotopic_mass, na.rm = TRUE), by = 2)) +
scale_y_continuous(name = "Retention Time (min)", limits = c(0, 19), breaks = seq(0, 19, by = 2)) +
labs(color = "Log10(Intensity)", shape = "Ladder Type", size = "Ladder Type") + # Add size to legend
theme_classic() +
theme(
axis.title.x = element_text(size = 12),
axis.title.y = element_text(size = 12),
axis.text.x = element_text(size = 10),
axis.text.y = element_text(size = 10),
legend.title = element_text(size = 10),
legend.text = element_text(size = 10)
) +
scale_color_gradientn(colors = turbo(256)) + # Use turbo color scale for the color aesthetic
scale_size_identity() # Use the actual values in point_size for sizing
## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`geom_point()`).
## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`geom_line()`).

df = read_xlsx("Data/sgRNA/Figure5/N100_mixture_result/100NM_19/100NM19_plot.xlsx") %>%
mutate(log_intensity = log10(sum_intensity))
plot_ly(df,
x = ~monoisotopic_mass,
y = ~apex_rt,
z = ~log_intensity,
color = ~sgRNA,
type = "scatter3d",
mode = "markers",
marker = list(size = 5)) %>%
layout(scene = list(
xaxis = list(title = "Monoisotopic Mass (Da)"),
yaxis = list(title = "Time (min)"),
zaxis = list(title = "Log Intensity")
))
## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels
## Warning in RColorBrewer::brewer.pal(N, "Set2"): minimal value for n is 3, returning requested palette with 3 different levels